计算机与现代化Issue(9)：1-7,7.DOI:10.3969/j.issn.1006-2475.2024.09.001
隐性角色下的协同推荐算法
Collaborative Recommendation Algorithm with Implicit Roles
摘要
Abstract
This article aims to improve the effectiveness of the algorithm,starts from the psychological needs of users,locates the implicit role group of users,and researches the personalized recommendation algorithms.From a theoretical point of view,the research in this paper effectively ensures the diversity requirements of recommendation systems and improves the accuracy of algorithms to a certain extent.It expands the relevant theory of implicit preference to address the phenomenon of preference evolu-tion.Through verification in real data,multiple experimental evaluation indicators have been significantly improved.This not only provides a theoretical basis and reference for recommendation systems,but also improves the accuracy of recommendation results.It has broad application prospects.From a practical point of view,the classification of users in this article is no longer limited to ordinary social attributes,but can further explore users'psychological needs,obtains more accurate and diverse rec-ommendation results,improves user satisfaction and experience.Enterprises can guide users to change their interests,increase their loyalty and value,improve their lifecycle,and increase their profits.关键词
推荐算法/隐性角色/电影推荐/推荐效果Key words
recommendation algorithm/implicit role/film recommendation/recommended effect分类
信息技术与安全科学引用本文复制引用
于天一,李剑锋,陈海龙,翟军..隐性角色下的协同推荐算法[J].计算机与现代化,2024,(9):1-7,7.基金项目
国家自然科学基金资助项目(72271037) （72271037）
中央高校基本科研业务费专项资金资助项目(3132019353) （3132019353）
